Event History Analysis with R

Event History Analysis with R, Second Edition, is an introduction to survival and event history analysis using real-life examples. It focuses on the analysis of large and complex datasets, with two new chapters on explanatory variables and regression and updates to the computing in the supporting R package. It is an excellent resource for researchers and practitioners of applied event history analysis and survival analysis.

Format: Paperback / softback
Length: 304 pages
Publication date: 29 January 2024
Publisher: Taylor & Francis Ltd

Event History Analysis with R, Second Edition, is a comprehensive guide to survival and event history analysis, focusing on social science applications. Since the first edition's publication, the field has shifted towards analyzing large and complex datasets, leading to innovative methods for tabulating and analyzing data with precision and power. This approach allows for the sharing of sensitive data without compromising integrity.

The second edition of this book expands on the content of the first, offering improved methods and introducing new ones. It includes two new chapters: Explanatory Variables and Regression and Register-Based Survival Data Models. The book has been restructured to enhance its flow, and significant updates have been made to the computing capabilities in the accompanying R package.

Key Features:

Introduction to survival and event history analysis, covering Cox regression for solving problems with incomplete data.
Parametric proportional hazards models, including Weibull, Exponential, Extreme Value, and Gompertz distributions.
Parametric accelerated failure time models with various distributions, such as Lognormal, Loglogistic, Gompertz, Exponential, Extreme Value, and Weibull.
Proportional hazards models for occurrence/exposure data, suitable for tabular and register-based data with extensive observed events.
Special treatments for external communal covariates, selections from the Lexis diagram, and creating period and cohort statistics.
"Weird bootstrap" sampling method for Cox regression with small to medium-sized data sets.
Supplemented by an R package (https://CRAN.R-project.org/package=eha), providing code and additional resources for readers.

Event History Analysis with R, Second Edition, is an essential resource for researchers and practitioners in social science, statistics, and medical fields who seek to analyze survival and event history data with precision and efficiency.

Weight: 494g
Dimension: 150 x 235 x 20 (mm)
ISBN-13: 9781032123202
Edition number: 2 ed